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Deep Learning in Medical Image Classification
Published in R. Sujatha, S. L. Aarthy, R. Vettriselvan, Integrating Deep Learning Algorithms to Overcome Challenges in Big Data Analytics, 2021
Problems, such as, irritation, hemorrhage, disease, and cancer in the gastrointestinal tract are the main causes of indigestion and improper absorption. Peptic or stomach ulcer is the bleeding caused in the upper GI tract. Tumors, gastric cancer, and colonic diverticulitis cause large bowel hemorrhage. Because of abnormal blood vessels, celiac sprue, Crohn’s illness, gastric tumors, peptic ulcers, and GI bleeding are issues that trouble the small intestine. Current imaging innovations such as endoscopy, enteroscopy, endoscopy of remote cases, tomography, and MRI play a huge role in the determination of these gastrointestinal tract issues.
Homo Sapiens (“Us”): Strengths and Weaknesses
Published in Michael Hehenberger, Zhi Xia, Huanming Yang, Our Animal Connection, 2020
Michael Hehenberger, Zhi Xia, Huanming Yang
The human digestive system consists of the gastrointestinal tract and other organs of digestion such as the tongue, salivary glands, pancreas, liver, and gall bladder. The process of digestion has many stages, the first of which starts in the mouth. Digestion involves the breakdown of food into smaller and smaller components, until they can be absorbed and assimilated into the body.
Homo Sapiens (“Us”): Strengths and Weaknesses
Published in Michael Hehenberger, Zhi Xia, Our Animal Connection, 2019
The human digestive system consists of the gastrointestinal tract and other organs of digestion such as the tongue, salivary glands, pancreas, liver, and gall bladder. The process of digestion has many stages, the first of which starts in the mouth. Digestion involves the breakdown of food into smaller and smaller components, until they can be absorbed and assimilated into the body.
Detection and classification of gastrointestinal disease using convolutional neural network and SVM
Published in Cogent Engineering, 2022
Melaku Bitew Haile, Ayodeji Olalekan Salau, Belay Enyew, Abebech Jenber Belay
The digestive system consists of the gastrointestinal tract and other organs which help the body to break down and absorb food. The gastrointestinal tract may be affected by a variety of diseases which affect its functionality. The domain of gastrointestinal endoscopy includes the endoscopic diagnosis of various digestive diseases using image analysis and various devices. Endoscopy is currently the preferred method for examining the gastrointestinal tract; however, previous studies have shown that there is a need for improvement as some classes are more difficult to identify than others. In this study, we proposed a concatenated neural network model by concatenating the extracted features of VGGNet and InceptionNet networks to develop a gastrointestinal disease diagnosis model. The deep convolutional neural networks VGGNet and InceptionNet are trained and used to extract features from the given endoscopy images. The proposed model achieves a classification accuracy of 98% and Matthews’s Correlation Coefficient of 97.8%, which is a significant improvement over previous techniques and other neural network architectures.